Transductive learning, first described by Vapnik (Vapnik, 1998) also describes a setting where both labeled and unlabeled data are used jointly to decide on a label assignment to the unlabeled data points.
the goal here is not to learn a general classification function that can be applied to new test sets multiple times but to achieve a high-quality onetime labeling of a particular data set.