If you have some application for which you need to ignore NaNs rather than take them into account, you could replace them with some other value which is easily identifiable as non-data. For example:
A(isnan(A)) = Inf;
A = unique(A,'rows');
A(isinf(A)) = NaN;
It's a little hackish. I know there are various toolbox functions, like nanmean and nanstd, which calculate other statistics of a dataset while ignoring NaNs. But there is no nanunique or nansort. Also, the work in unique is done by calling sortrows which calls a MEX file, so you can't just edit it to take NaNs into account. So the above code seems like the cleanest quick solution.