Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it.
Oversampling is capable of improving resolution and signal-to-noise ratio, and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.
A signal is said to be oversampled by a factor of N if it is sampled at N times the Nyquist rate.
[1] Without oversampling, it is very difficult to implement filters with the sharp cutoff necessary to maximize use of the available bandwidth without exceeding the Nyquist limit.
By increasing the bandwidth of the sampling system, design constraints for the anti-aliasing filter may be relaxed.
: This averaging is only effective if the signal contains sufficient uncorrelated noise to be recorded by the ADC.
In similar cases where the ADC records no noise and the input signal is changing over time, oversampling improves the result, but to an inconsistent and unpredictable extent.
Certain kinds of ADCs known as delta-sigma converters produce disproportionately more quantization noise at higher frequencies.
By running these converters at some multiple of the target sampling rate, and low-pass filtering the oversampled signal down to half the target sampling rate, a final result with less noise (over the entire band of the converter) can be obtained.
The term oversampling is also used to denote a process used in the reconstruction phase of digital-to-analog conversion, in which an intermediate high sampling rate is used between the digital input and the analog output.
Essentially, this is a way to shift some of the complexity of reconstruction from analog to the digital domain.
Oversampling in the ADC can achieve some of the same benefits as using a higher sample rate at the DAC.