If you can apply any kind of approach that automatically feeds measurements of user success back in to an algorithm to automatically adjust e.g. the colors used for the gradient based on measuring what works best, you can justify saying you're using machine learning.

I think people are too often too quick to assume that machine learning necessarily implies deep learning and neural networks, when often it can reasonably be reduced to simple statistical approaches.