Its up to the Team Pytorch @ptrblck may have a better answer as to why.
It maybe that the Cuda11 was released back in May, and the codebase was tested on it. Cuda11.1 was released around september 23 I guess, around 1 month before releasing the stable 1.7.
So it makes sense to stick to the version you have been working on for the past couple of months and not make yourself deal with some probable regression/bugs caused by the new update. (take into account the OSes, drivers, etc as well)
If  there is a need for bleeding edge cuda, anyone can easily build from source and call it a day. For the majority of users though the stability is the primary goal.
Nevertheless, we will be expecting a 1.7.1 in a near future (possibily in December?) and that might include cuda 11.1 I’m not sure though.
Again as I stated earlier, you can always build Pytorch against the latest cudatoolkit and enjoy it. the build process is pretty easy to follow and usually is very straightforward.
Cheers.