How does KMeans converge and what are its limitations?

KMeans converges by iteratively updating centroids until assignments stabilize.

It alternates between assigning points to nearest centroid and recomputing centroids. Convergence occurs when assignments no longer change or centroid movement is below threshold. However, it is sensitive to initialization and assumes spherical clusters of similar density.