Audio Broadband Noise Detection
The algorithm is basically based on the assumption that noise is "white", ie. in the expectation value, the noise energy in every DFT bin is equal. Under that assumption, and assuming a "long enough" observation, there has to be the same noise floor in every bin.

Sound on the other hand, is a highly correlated signal. So the assumption is that there's at least one DFT bin at a time where there's no significant sound signal.

As you might imagine, that's a bit of an oversimplification on both sides: There's a lot of music that actually uses Noise, or broadband signals, and audio noise typically is everything but white. 

In essence: this boils down to the good ol' "What is my SNR?" question:

You, as the DSP designer, will have to model your signal, and your noise. After that, the question kind of answers itself. It's really more of a question of semantics than engineering: For example, take psychedelic rock/stoner/doom metal: wideband noise in the string instrument's track is very essential to that genre; is it noise, then? And if you get a recording of a classical guitar piece, wouldn't you consider the same noise in the signal part of the noise or music energy?