Meh, most Bayesian techniques still assume a model. It's more like:

Assuming a model M characterized by parameters T and giving rise to data Y, what is P(T|Y,M)

To be sure, you can compare the probability of models as well, and there are Bayesian semiparametric techniques, but models are still really important.