If a K-NN ($ k $ Nearest Neighbors) Algorithm Performs Very Well for Low $ k $, Can Something Be Inferred About the Data Set?
If the result is consistent with a large test set than it means your training data is dense and well define the degrees of freedom of the problem.

If the training set was small it means there is a good separation between your classes in space.