From the way I'm understanding the question, I pre-assume that you know that Watson conversation and Natural Language classifiers (NLC) are two different services provided by IBM Watson.
Watson conversation will basically help you build a chatbot or a bot (which has speech to text or vice-versa). This chatbot helps users in different ways. Let's say if a user asks a question to the chatbot, chatbot will answer accordingly (It depends on how you designed the dialogs/ or the responses) to the question asked.
Question 1: What's your name?
Answer 1: I'm Watson.
Instead, if the question was asked incorrectly.
Incorrect question : Wat is ur name?
Answer would still be: I'm Watson.
In order to build a chatbot using Watson conversation, you need to make sure that you have proper understanding of Intents, Entities, and most importantly Dialogs (Dialogs help you design the flow of the conversation). If you know these 3 parts then you are good to go with Watson conversation. There's no link between NLC and Watson conversation if you keep them isolated. *That being said, Watson conversation itself has an Natural language understanding where it could figure out User questions even if the questions are **incomplete, grammatically incorrect, mis-spelled words etc.*
In short, you need not bind anything (Natural language) to make the conversation start working. Just focus on those 3 (Intent, entities, & dialog) portions provided and you are good to go.