You don't understand.
You have a (possibly infinite) set of hypotheses. You maintain beliefs about this set. As you get more data, your beliefs change. To maintain beliefs you need a distribution/density. To do that you need a model (a model is just a set of densities you consider). You may have a flexible model and let the data decide how flexible you want to be (non-parametric Bayes stuff, I don't know too much about it), but there's still a model.
Suggesting for the third and final time to get off the internet argument train and go read a book about Bayesian inference.
Oh, sorry I misunderstood your argument. That's an interesting solution.
If it's worth saying, but not worth its own post (even in Discussion), then it goes here.
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