The Encoder-Decoder structure is a neural network architecture primarily used for sequence-to-sequence tasks, where the encoder processes the input sequence into a context vector and the decoder generates the output sequence from this vector. This architecture is fundamental in applications like machine translation, where it allows for flexible handling of variable-length input and output sequences.