Why do embeddings suffer from hubness in high dimensions?

Some points become overly frequent nearest neighbors (hubs).

In high-dimensional spaces, distributional asymmetry causes certain points to appear as nearest neighbors to many others. This hubness phenomenon degrades retrieval diversity and biases similarity search systems.