In graphics, MSAA is a technique where you take multiple samples of something per pixel and then average the values to get the final pixel value. The image quality improves as a result, and its considered a form of anti aliasing. Does this technique have an equivalent in audio samples or other 1d data streams?
Oversampling of audio can be used to reduce aliasing artifacts that result from non-linear processing. Harmonics generated by the nonlinear process can be filtered from the oversampled signal by a lowpass filter. A graphics analog of this is supersampling. If Wikipedia is to trust, multi-sample antialiasing is a further optimization in which only the mixing proportion of background and foreground is calculated at each edge pixel of the foreground object, using supersampling.
An analogous audio problem would be implementation of amplitude modulation by a square wave. Hearing is more sensitive to frequency domain errors than vision, which operates more in the spatial domain. Linear cross-fading at the sample point nearest to each square wave edge would create a beating artifact that for each overtone would have an amplitude proportional to its amplitude and squared frequency. For a high-enough fundamental frequency of the square wave, the artifact would be audible, demanding the use of another method with better frequency domain behavior.
No. The reason is that MSAA works in the visual domain. Optically, we have hardwired edge detectors. MSAA eliminates unintended edges in generated images.
Acoustically, we do not have such edge detectors, and therefore there's no reason to remove them. Also, loudspeakers already filter out such edges mechanically.