diff --git a/CHANGELOG.md b/CHANGELOG.md
index 279c912c05..d1b9ea68b0 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -17,6 +17,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 * Re-enable flaky BWC test testKNNWarmupCustomLegacyFieldMapping and restore legacy index settings in BWC test fixtures [#2415](https://github.com/opensearch-project/k-NN/issues/2415)
 
 ### Bug Fixes
+* Return a non-matching explanation from `KNNWeight.explain()` for documents that are not nearest neighbors [#3480](https://github.com/opensearch-project/k-NN/pull/3480)
 * Preserve raw non-XContent `_source` fields when derived source is enabled [#3402](https://github.com/opensearch-project/k-NN/pull/3402)
 * Fix dimension-based oversampling not applying for 32x compression [#3455](https://github.com/opensearch-project/k-NN/pull/3455)
 * Fix NPE in nested kNN search when index contains documents without nested object [#3368](https://github.com/opensearch-project/k-NN/pull/3368)
diff --git a/src/main/java/org/opensearch/knn/index/query/KNNWeight.java b/src/main/java/org/opensearch/knn/index/query/KNNWeight.java
index 675f19211f..0207a4fae6 100644
--- a/src/main/java/org/opensearch/knn/index/query/KNNWeight.java
+++ b/src/main/java/org/opensearch/knn/index/query/KNNWeight.java
@@ -133,7 +133,13 @@ public Explanation explain(LeafReaderContext context, int doc, float score) {
             // calculate score only when its 0 as for disk-based search,
             // score will be passed from the caller and there is no need to re-compute the score
             if (score == 0) {
-                score = getKnnScore(knnScorer, doc);
+                // explain() can be called for a document this query does not match, for instance when the knn clause is
+                // one of several should clauses. Reporting a match for such a document breaks the contract that
+                // Weight.explain() and the scorer of the same Weight have to agree on which documents match.
+                if (knnScorer.iterator().advance(doc) != doc) {
+                    return Explanation.noMatch("the document is not a nearest neighbor result for the field [" + knnQuery.getField() + "]");
+                }
+                score = knnScorer.score();
             }
         } catch (IOException e) {
             throw new RuntimeException(String.format("Error while explaining KNN score for doc [%d], score [%f]", doc, score), e);
@@ -273,10 +279,6 @@ private Scorer getOrCreateKnnScorer(LeafReaderContext context) throws IOExceptio
         return scorer;
     }
 
-    private float getKnnScore(Scorer knnScorer, int doc) throws IOException {
-        return (knnScorer.iterator().advance(doc) == doc) ? knnScorer.score() : 0;
-    }
-
     @Override
     public ScorerSupplier scorerSupplier(LeafReaderContext context) {
         return new ScorerSupplier() {
diff --git a/src/test/java/org/opensearch/knn/index/query/ExplainTests.java b/src/test/java/org/opensearch/knn/index/query/ExplainTests.java
index 3eac94cbd5..d05a7ad324 100644
--- a/src/test/java/org/opensearch/knn/index/query/ExplainTests.java
+++ b/src/test/java/org/opensearch/knn/index/query/ExplainTests.java
@@ -37,6 +37,7 @@
 
 import java.io.IOException;
 import java.util.ArrayList;
+import java.util.Collections;
 import java.util.Comparator;
 import java.util.List;
 import java.util.Locale;
@@ -376,6 +377,54 @@ public void testDefaultANNSearch() {
         assertTrue(Comparators.isInOrder(actualDocIds, Comparator.naturalOrder()));
     }
 
+    @SneakyThrows
+    public void testExplain_whenDocIsNotANearestNeighbor_thenNoMatch() {
+        // Given
+        int k = 3;
+        jniServiceMockedStatic.when(
+            () -> JNIService.queryIndex(anyLong(), eq(QUERY_VECTOR), eq(k), eq(HNSW_METHOD_PARAMETERS), any(), eq(null), anyInt(), any())
+        ).thenReturn(getFilteredKNNQueryResults());
+
+        final int[] filterDocIds = new int[] { 0, 1, 2, 3, 4, 5 };
+        final Map<String, String> attributesMap = ImmutableMap.of(
+            KNN_ENGINE,
+            KNNEngine.FAISS.getName(),
+            SPACE_TYPE,
+            SpaceType.L2.getValue()
+        );
+
+        setupTest(filterDocIds, attributesMap);
+
+        final KNNQuery query = KNNQuery.builder()
+            .field(FIELD_NAME)
+            .queryVector(QUERY_VECTOR)
+            .k(k)
+            .indexName(INDEX_NAME)
+            .filterQuery(FILTER_QUERY)
+            .methodParameters(HNSW_METHOD_PARAMETERS)
+            .vectorDataType(VectorDataType.FLOAT)
+            .explain(true)
+            .build();
+        query.setExplain(true);
+
+        final KNNWeight knnWeight = new DefaultKNNWeight(query, 1f, filterQueryWeight);
+        final KNNScorer knnScorer = (KNNScorer) knnWeight.scorer(leafReaderContext);
+        assertNotNull(knnScorer);
+        knnWeight.getKnnExplanation().addKnnScorer(leafReaderContext, knnScorer);
+
+        // The query returns FILTERED_DOC_ID_TO_SCORES, so this document is not one of the nearest neighbors. Advancing
+        // the scorer to it lands on the next matching document instead.
+        final int docIdWithoutMatch = Collections.min(FILTERED_DOC_ID_TO_SCORES.keySet()) - 1;
+
+        // When
+        final Explanation explanation = knnWeight.explain(leafReaderContext, docIdWithoutMatch);
+
+        // Then
+        assertNotNull(explanation);
+        assertFalse(explanation.isMatch());
+        assertTrue(explanation.getDescription().contains(FIELD_NAME));
+    }
+
     @SneakyThrows
     public void testANN_FilteredExactSearchAfterANN() {
         ExactSearcher mockedExactSearcher = mock(ExactSearcher.class);