If similarity is learned incorrectly, what breaks in KNN systems?

The entire model collapses because KNN depends entirely on similarity correctness.

KNN has no internal correction mechanism. If similarity is misdefined, all downstream predictions are wrong. This makes metric choice and feature representation critical to system correctness.