I don't know much about Solomonoff induction, so I may be wrong about this, but is it not the case that the universal prior only takes into account computable functions which exactly output the sensory data? If that is the case, consider the following scenario:

We have a function F which takes an unbounded natural number N as input and is provably uncomputable for all valid inputs. We have a computable algorithm A which provably outputs lower and upper bounds for F for any valid input. Furthermore, it is provable that no computable algorithm can provably produce tighter bounds on F's output than A (regardless of N). We can see that A outputs the bounds for a closed interval in the set of real numbers. We know that all such intervals (for which the lower and upper bounds are not equal) are uncountable. Now imagine a physical hypercomputer which outputs F(0), then F(1), then F(2), etc. to infinity. No computable algorithm will be able to predict the next symbol output by this hypercomputer, but there will be computable minds capable of recognizing the pattern and so of using A to place stronger bounds on its predictions of future sensory experience than AIXI can.

EDIT: Actually, this scenario might be broken. Specifically, I'm not sure what it physically means to 'output' an uncomputable number, and I think that AIXI's problem dissolves if we limit ourselves to the computable (and thus countable) subsets of the output intervals.