Why does k-means have more bias than spectral clustering and GMM?

Question

I ran into a 2019-Entrance Exam question as follows:

Which of the following algorithm has the higher bias?

1. GMM
2. GMM (identity covariance matrix)
3. spectral clustering
4. k-means

The answer mentioned is (4), but some search on google showed me maybe (1) and (2) is equal to (4). Why would k-means be the algorithm with the highest bias? (Can you please also provide references to valid material to study more?)