The first is if you have multiple people accepting applicants and some of them are biased to the point of not accepting applicants of particular types. That means all the applicants that are discriminated against that did make it were simply selected by people who weren't biased, and therefore won't outperform anyone.
The second is if the actual selection process is somewhat random instead of being based on pure performance. The ones who make it through that process won't necessarily perform any better, they'll just be luckier.
The third is if the application process accepts everyone equally, and then randomly prunes out people according to a bias. This is similar to the second except the acceptance criteria is still performance-based, but because it randomly throws out people (instead of throwing out low-performers), the remaining people are still going to perform the same as those who were not pruned.
The first footnote on the page also points out that if the selection criteria are different for the different groups then this process won't work, which seems like a pretty important caveat that I wish was in the article proper. One really common form of bias (especially in tech) is being biased against women, and that's also a situation where it's very common to (unconsciously or otherwise) use appearance in judging female applicants but ignore appearance for male applicants.