How would you explain KNN limitations using geometry alone?

KNN fails when geometric proximity does not align with semantic similarity.

KNN assumes Euclidean proximity reflects meaning. In high-dimensional or manifold data, geometry becomes distorted, and nearest neighbors are not semantically meaningful.