A key concept with Sigma Delta is "noise shaping". With a typical data converter the quantization noise is uniformly distributed across the primary
Nyquist frequency range of $-f_s/2$ to $+f_s/2$. Oversampling results in the same noise (which is dependent on the number of bits used) spread over a wider frequency range, such that the power spectral density (watts/Hz) reduces. Filtering thus reduces the overall noise, which is the equivalent of increasing the effective number of bits. That said we can gain 1/2 a bit for every doubling of frequency: If we double the frequency, the noise power is spread by a factor of two, so the noise density drops by a factor of 2 in power which is 3 dB, assuming we properly filter out the higher frequency noise.
With the Sigma Delta, the same thing occurs, but a feedback processes shapes the noise such that it is much lower as the spectrum approaches the lower frequencies (DC), and higher at the higher frequencies (same total noise power, but shaped to favor the lower frequencies). Thus when we low pass filter (with a digital filter for a sigma delta ADC), the output of the filter can be a much higher number of bits, given the reduced quantization noise in the spectrum of the filters output.
Every order adds another 6 dB/octave of SNR improvement. A direct ADC has 3 dB/octave as described above. A first order sigma delta has 9 dB/octave (but suffers from pattern noise, not advised to use), a second order sigma delta has 15 dB/octave, a third order has 21 dB/octave etc. 5th order sigma deltas are not uncommon as commercial solutions.