Why is K-Means sensitive to outliers?

Outliers distort centroid positions because the mean is highly sensitive to extreme values.

Since centroids are computed as arithmetic means, a single extreme point can shift cluster centers significantly. This leads to incorrect assignments and unstable clusters.