Random forest on classification

The XGB documentation states that

For instance, objective will typically be reg:squarederror for regression and binary:logistic for classification

Since binary:logistic merely accepts 0 and 1 as labels. Do random forests in XGBoost merely work on binary classification?

The objective should be set to multi:softprob when performing multi-class classification.

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