We consider the Unrestricted Bin Packing problem where we have bins of equal size and a sequence of items. The goal is to maximize the number of items that are packed in the bins by an on-line algorithm. We investigate the power of performing admission control on the items, i.e., rejecting items while there is enough space to pack them, versus behaving fairly, i.e., rejecting an item only when there is not enough space to pack it. We show that by performing admission control on the items, we get better performance for various measures compared with the performance achieved on the fair version of the problem. Our main result shows that with an unfair variant of First-Fit we can pack 2/3 of the items for sequences in which the optimal can pack all the items. This is in contrast to the standard First-Fit where we show a tight upper bound of 5/8.