I think the information theoretic approach to modeling concerns actually implies such "simpler is better" approaches as Occam's Razor. At least that's my take on [http://arxiv.org/abs/cond-mat/9601030], which derives a quantitative form of it.
I haven't read that paper, and the abstract makes my head spin! I'll have a look later, and try and figure out the argument. I agree with you that things like the I-measure are based on the idea that simpler is good, and it works well in practice - both in Machine Learning and in the real world - which is why humans tend to prefer it. But (the paper you cite aside) I don't know of a deep reason why simple is preferred by nature.
Also there is a deep cognitive bias here, perhaps we lack the machinery to understand the world as it really is!
