to have points as training samples they need to have the followings attribute structure
ID, class
1, forest
2, forest
3, water
4, urban
5, forest
6, urban
…
If you manage to convert the attributes of your KML imported into QGIS into this structure, SNAP will recognize it correctly.
As collecting a sufficient number of training points can be exhausting, maybe these considerations help you as well: Number of training samples at Random forest classifier