I don't think you can back that claim up. ML models as often used can't escape their programming. But I don't see any fundamental reason you can't loop one back on itself.
Isn't this already done to some extent by using a model to assess its own output versus the current environmental state? Recurrent models combined with reinforcement learning actually look a lot like what you're claiming can't be done.
> There is no mental model of the world to rationalize against
There's a theory and some associated research about a model that performs well necessitating an internal model that accurately reflects the environment in which it operates. Or something like that. Sorry I can't recall the paper off the top of my head.
> Whatever tasks a ML model has been deliberately programmed with
Yeah, no, that's not the case. See the entire field of reinforcement learning.