Machine Learning Crash Course: The Bias-Variance Dilemma 9 years ago
In my opinion, the real problem in that case was not the overfitting, but that they extrapolated from that data. They didn't have anything above Magnitude 8. (https://ml.berkeley.edu/blog/assets/tutorials/4/earthquake-f...)
You should never, ever extrapolate. It doesn't matter what your model is, it won't work.
On a side note, it could be that there is a breakpoint at Magnitude 7.25, where the slope of the line really changes, and a segmented linear regression is appropriate (https://en.wikipedia.org/wiki/Segmented_regression). But we would need more data to be sure, anyway.