What happens if K is set too high or too low?

Too small K underfits clusters, while too large K overfits and creates fragmented clusters.

Low K merges distinct groups, increasing intra-cluster variance. High K splits natural clusters into smaller artificial groups, reducing interpretability and increasing sensitivity to noise.