If you have many features, likely meaning many columns in your table of data, then you could try clustering.

Something as simple as k-Nearest Neighbours could work nicely.

You would first fit a model using your available data, then look at the resulting clusters. Each cluster will represent combinations of your features.

Next you can put new data points into the model and it will tell you to which cluster it would best fit.

This would actually be a fully fledged predictive model! It is unsupervised, because you are not using and predictive labels