I guess it's a Principle Component Analysis (PCA) dimensionality reduction so the axes are not necessarily concepts/features with names. More just "abstract dimensions of similarity."
The underlying UMAP model is actually pretty interesting. It's linked to in the tour, though I would have expected it to be featured more prominently: https://pair-code.github.io/understanding-umap/