How does Random Forest interact with label smoothing effects implicitly?

RF produces implicit label smoothing through vote averaging across trees.

Each tree outputs a hard or soft class prediction. Averaging across trees produces probabilistic outputs that resemble label smoothing, reducing overconfidence. This improves generalization by preventing extreme probability assignments unless consistently supported across many trees.