How do random projections help mitigate curse of dimensionality?

They preserve distances approximately while reducing dimensionality.

Johnson-Lindenstrauss lemma guarantees that random linear projections preserve pairwise distances within small distortion, making them powerful for scalable ML in high dimensions.