Think of it this way, the yolo algorithm works via a NxN grid system, for example if we have a 13x13 grid and 3 anchors per grid that's 3 * 13 ^ 2 meaning 507 different cells, each having it's own object presence score.

If you only have say 5 objects that means that out of those 507 presence scores only 5 are told to predict that there's an object, and due to this class imbalance the model finds it much easier to prioritize those 502 other presence scores where there is no object since there's simply so many of them.

And the noobj lambda is meant to combat the class imbalance between cells with and without an object