IIRC it depends on the structure of your data. From what I understand, it slowly expands the hypersphere of contained points in bursts (grabbing further and further tree branches), sorting them in order of relevancy as it goes. It depends on whether you don't have to do an extra expansion to get the extra points. An iterator for 200, then getting 150, will be slower than getting an iterator for 150, but chances are it will be faster than getting an iterator for 200 and using all 200.
Pretty much yeah, though it does avoid the full effort of sorting them by using a min-max heap that tosses the most distant points off and keeps the closest point accessible in constant time. The search algorithm is exactly the same as searching for all 200 (it needs to remember the 200 closest points it's found so far, and know what the furthest and closest ones of that set are), except that it pauses the search when when it is able to determine that no unchecked branch could have anything closer than the closest point not yet returned by the iterator.