On the ML front (which is probably their primary motivation) it's pretty useful for the kind of things Spotify is interested. As a basic example, say you want to train a model to classify songs by genre. If you have say, a country song, adding a bit of reverb or compression to it will not change what genre it sounds like. So augmenting their training data with small transformations such as these can make their models more robust to these transformations. Obviously, this has to been judiciously, e.g, if you add tons of distortion and reverb to a country song it might sound like some experimental noise and not country. This kind of thing also can help with duplicate detection, song recommendations, playlist generation, autotagging, etc.

As for creators, maybe not a large fraction of music creators are coders, but there's certainly an intersection in that venn diagram, though I have no idea how large it is. And I imagine this could be used to create other tools that don't require coding.

Clearly, most of the time it makes more sense to apply FX interactively in your DAW of choice, but I find it useful to programmatically modify audio sometimes. For example, I've written quick scripts using sox and other tools to normalize/resample audio, as well as slice loops. I could see being able to add other fx such as compression or maybe even reverb programatically could be occasionally useful.